#!/usr/bin/env python
import FreeSimpleGUI as sg
import datetime
import calendar
import forecastio

'''
    Example of a weather App, using:
    - DARKSKY
    - google maps coordinates
    Copright 2020, 2022 PySimpleGUI

'''



##### CHANGE these settings to match your location... check Google Maps #####
MY_LOCATION_LAT = 35.000000
MY_LOCATION_LON = -79.000000
# MY_LOCATION_LAT = 37.7568
# MY_LOCATION_LON = -87.1191
# MY_LOCATION_LAT = 41.5726

# MY_LOCATION_LON = -93.6102


##### You need a free dark-sky key. You get 1000 calls a month for free #####
# *** INSERT YOUR DARKSKY KEY HERE **
DARKSKY_KEY = "INSERT YOUR DARKSKY KEY HERE!"


NUM_COLS = 8                    # Changes number of days in forecast
USE_CELCIUS = False

class GUI():
    def __init__(self, location):
        self.api_key = DARKSKY_KEY
        self.lat = MY_LOCATION_LAT
        self.lng = MY_LOCATION_LON
        self.blink_count = 0

        sg.set_options(border_width=0, text_color='white',
                       background_color='black', text_element_background_color='black')

        # Create clock layout
        clock = [
            [sg.T('', pad=((220,0),0)),
             sg.Image(data=ledblank, key='-HOUR1-'),
             sg.Image(data=ledblank, key='-HOUR2-'),
             sg.Image(data=ledblank, key='-COLON-'),
             sg.Image(data=ledblank, key='-MIN1-'),
             sg.Image(data=ledblank, key='-MIN2-')], ]

        # Create the weather columns layout
        weather_cols = []
        for i in range(NUM_COLS):
            weather_cols.append(
                [[sg.T('', size=(4, 1), font='Any 20', justification='center', key='_DAY_' + str(i)), ],
                 [sg.Image(data=w1, background_color='black', key='-ICON-'+str(i), pad=((4, 0), 3)), ],
                 [sg.T('--', size=(3, 1), justification='center', font='Any 20', key='_high_' + str(i), pad=((10, 0), 3))],
                 [sg.T('--', size=(3, 1), justification='center', font='Any 20', key='_low_' + str(i), pad=((10, 0), 3))]])

        # Create the overall layout
        layout = [[sg.Column(clock, background_color='black')],
                  [sg.Column(weather_cols[x], background_color='black') for x in range(NUM_COLS)] + [sg.T('×',enable_events=True, key='Exit')] + [sg.T('C',enable_events=True, key='-CELCIUS-')],
                  # [sg.RButton('Exit', button_color=('black', 'black'),
                  #             image_data=orangeround, tooltip='close window', pad=((450,0),(10,0)))]
                  ]

        # Create the window
        self.window = sg.Window('DarkSky Weather Forecast Widget', layout,
                           background_color='black',
                           grab_anywhere=True,
                           use_default_focus=False,
                           no_titlebar=True,
                           alpha_channel=.8,            # set an alpha channel if want transparent
                           location=location,
                           right_click_menu=[[''], ['Edit Me', 'Exit',]],
                            enable_close_attempted_event=True,
                           finalize=True)

        self.colon_elem = self.window.find_element('-COLON-')
        self.hour1 = self.window.find_element('-HOUR1-')
        self.hour2 = self.window.find_element('-HOUR2-')
        self.min1 = self.window.find_element('-MIN1-')
        self.min2 = self.window.find_element('-MIN2-')

        self.window['Exit'].set_cursor('hand2')
        self.window['-CELCIUS-'].set_cursor('hand2')

    def update_clock(self):
        # update the clock
        now = datetime.datetime.now()
        real_hour = now.hour - 12 if now.hour > 12 else now.hour
        hour1_digit = led_digits[real_hour // 10]
        self.hour1.Update(data=hour1_digit)
        self.hour2.Update(data=led_digits[real_hour % 10])
        self.min2.Update(data=led_digits[int(now.minute) % 10])
        self.min1.Update(data=led_digits[int(now.minute) // 10])
        # Blink the :
        self.colon_elem.Update(data=ledcolon if self.blink_count %2 else ledblank)
        self.blink_count += 1

    def update_weather(self):
        forecast = forecastio.load_forecast(self.api_key, self.lat, self.lng)
        daily = forecast.daily()
        today_weekday = datetime.datetime.today().weekday()

        max_temps = []
        min_temps = []
        daily_icons = []
        for daily_data in daily.data:
            daily_icons.append(daily_data.d['icon'])
            max_temps.append(int(daily_data.d['temperatureMax']))
            min_temps.append(int(daily_data.d['temperatureMin']))

        for i in range(NUM_COLS):
            day_element = self.window.find_element('_DAY_' + str(i))
            max_element = self.window.find_element('_high_' + str(i))
            min_element = self.window.find_element('_low_' + str(i))
            icon_element = self.window.find_element('-ICON-' + str(i))
            day_element.Update(calendar.day_abbr[(today_weekday + i) % 7])
            max_temp = max_temps[i]
            min_temp = min_temps[i]
            if USE_CELCIUS:
                max_temp = int((max_temp-32)/1.8)
                min_temp = int((min_temp-32)/1.8)
            max_element.Update(max_temp)
            min_element.Update(min_temp)
            icon_data = weather_icon_dict[daily_icons[i]]
            # sg.Print(icon_data, wait=True)
            try:
                icon_element.update(icon_data)
            except:
                pass


def main():
    global USE_CELCIUS
    # Get the GUI object that is used to update the window
    location = sg.user_settings_get_entry('-location-', (None, None))

    gui = GUI(location)

    # ---------- EVENT LOOP ----------
    last_update_time = 0
    while True:
        # Wake up once a second to update the clock and weather
        event, values = gui.window.read(timeout=1000)
        if event in (None, 'Exit', sg.WIN_CLOSE_ATTEMPTED_EVENT):
            sg.user_settings_set_entry('-location-', gui.window.current_location())  # The line of code to save the position before exiting
            break
        elif event == '-CELCIUS-':
            USE_CELCIUS = not USE_CELCIUS
        elif event == 'Edit Me':
            sg.execute_editor(__file__)
        elif event == 'Last':
            sg.popup(gui.window.last_right_click_widget)
        # update clock
        gui.update_clock()
        # update weather once ever 6 hours
        now = datetime.datetime.now()
        if last_update_time == 0 or (now-last_update_time).seconds >= 60*60*6 or event == '-CELCIUS-':
            print('*** Updating Weather ***')
            last_update_time = now
            gui.update_weather()


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led4 = b'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'

led5 = b'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'

led6 = b'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'

led7 = b'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'

led8 = b'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'

led9 = b'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'

ledcolon = b'iVBORw0KGgoAAAANSUhEUgAAACUAAAA8CAYAAADhR3NQAAAACXBIWXMAADBKAAAwSgHCONjjAAABdklEQVRoge2YQU7DMBBFn9MEVVBYcADEmiVH4BScD3EL7gIcAYEEFSQdFrZRCJGYeBa1qnlSZSuVJz8/k/EkARAqo9m3gDlclBYXpcVFaXFRWlyUFhelpUpRrWVxAFaTYwIMlqApbnX9VJFT+UpOgRugA3ZE195C4EHE7JYs/TVpvAJ5BxGQPo1PTSObEASQUBA7xS/nE/hI8+yMEJ20YBK1G81zwnfWoKXr85MxAF9p3o/+24tT45N2k/EYOLIoovDpy069AvfAOdGxDngR+cmzUg6nTv0XoJ85toQqnapyQ3ZRWlyUFhelpUpR5oo+1xFYq3GVFd3Uo18Cd8CGuN+tgcem4VaErUjxFZtErYFr4ITY8K2AM2ILsy0JnDD36Pnk49a4mh49B2qtQUvX5zzZ8TdnVqVBR5jWD/x2C6Ko6av8UkwloQUuiImd32J64Bnb94TDqVNj5u7/9JYupUqnqtyQXZQWF6XFRWlxUVpclBYXpeUbS+1qOYf8HRgAAAAASUVORK5CYII='

ledblank = b'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w1 = b'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'

w2 = b'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w3 = 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w4 = 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w5 = 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'
orangeround = b'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'

weather_icon_dict = {'clear-day': w1, 'clear-night': w1, 'rain': w3, 'snow': w3, 'sleet': w3, 'wind': w3, 'fog': w3,
                     'cloudy': w4, 'partly-cloudy-day': w5, 'partly-cloudy-night': w5}

led_digits = [led0, led1, led2, led3, led4, led5, led6, led7, led8, led9]

if __name__ == '__main__':
    main()
